RESULTS FROM 1 TO 8 OF 8

2012, Contributo in volume, ENG

From human creative cognitive processes to adaptable artificial system design

Morgavi, Giovanna; Marconi, Lucia; Morando, Mauro; Cutugno, Paola

In epigenetic robotics, a new research field, interdisciplinary theory and empirical evidences are used to inform adaptive robotic models, and, vice-versa, these models can be used as tools to make experimental predictions in developmental psychology. A truly autonomous robot should be capable of evolving and `growing up' through experience. Following different psychological points of view, growing up implies a knowledge creative process called: change of functional meaning; increased complexity; enlargement of the internal knowledge map; abstraction and insight. To understand this creative process, we organized an experiment with pre-school children diving with the abstraction process. The cognitive development of children of this age do not include the ability of abstraction, but they are able to explain the process they are thinking. Forty-two metaphoric sentences have been proposed to eight working-groups, of nine to ten children each, asking for their abstracted meanings. After a preliminary "brainstorming" phase , where the free creative associations were prevalent, we addressed children's attention towards the individuation of the metaphoric meaning. The process has been recorded and then we analyzed and classified the answers. Collective speech have been analyzed to compensate the individual differences. The children disclosure was mostly driven by their value system, their motivations and their emotions. They tried many different strategies to reach the abstract meaning, starting from their concrete knowledge and experiences. Each children followed a set of thinking paths that resulted in some very interesting suggestions for the architecture of an adaptive and evolving robot: i.e. the importance of multi-sensor perception, motivation and emotional drives are underlined and, the growing up insights shows similarities to emergent self-organized behaviours.

DOI: 10.4324/9780203325988

2009, Abstract in atti di convegno, ENG

From creative cognitive learning to adaptable artificial system design

Morgavi Giovanna; Marconi Lucia; Morando Mauro; Cutugno Paola

Background: Over the last decade, a number of researchers have suggested a developmental perspective on AI and robotics. The ultimate shared goal among them seems to be the idea of bootstrapping high-level cognition through a process in which the agent interacts with a real physical environment over extended periods of time [2]. These studies generated epigenetic robotics, a new AI/ robotics field which includes the two-fold goal of understanding biological systems by the interdisciplinary integration between social/life and engineering sciences and, simultaneously, that of enabling robots and other artificial systems to autonomously develop skills for any particular environment (instead of programming them to solve particular goals for a specific environment). Interdisciplinary theory and empirical evidence are used to inform epigenetic robotic models, and these models can be used as theoretical tools to make experimental predictions in developmental psychology and other disciplines studying cognitive development in living systems. One of the fundamental methodological assumptions is that cognition is embodied, which means that it arises from bodily interactions with the real world[1]. The next logical step along the road towards truly autonomous robots that can dive in unpredictable environments is to investigate how one might design robots that are capable of `growing up' through experience. A living artifact grows up when its capabilities, abilities/knowledge, shift to a further level of complexity [3]. Following different psychological points of view, growing up implies: adaptation, change of functional meaning; increased complexity; enlargement of the internal knowledge map; ; abstraction and insight.

CEM09 International Congress on Cognition, Emotion & Motivation, Hammamet, Tunisia, 2-5 Novembre 2009

2009, Contributo in atti di convegno, ENG

From creative cognitive learning to adaptable artificial system design

Morgavi Giovanna; Marconi Lucia; Morando Mauro; Cutugno Paola

Background: Over the last decade, a number of researchers have suggested a developmental perspective on AI and robotics. The ultimate shared goal among them seems to be the idea of bootstrapping high-level cognition through a process in which the agent interacts with a real physical environment over extended periods of time [2]. These studies generated epigenetic robotics, a new AI/ robotics field which includes the two-fold goal of understanding biological systems by the interdisciplinary integration between social/life and engineering sciences and, simultaneously, that of enabling robots and other artificial systems to autonomously develop skills for any particular environment (instead of programming them to solve particular goals for a specific environment). Interdisciplinary theory and empirical evidence are used to inform epigenetic robotic models, and these models can be used as theoretical tools to make experimental predictions in developmental psychology and other disciplines studying cognitive development in living systems. One of the fundamental methodological assumptions is that cognition is embodied, which means that it arises from bodily interactions with the real world[1]. The next logical step along the road towards truly autonomous robots that can dive in unpredictable environments is to investigate how one might design robots that are capable of `growing up' through experience. A living artifact grows up when its capabilities, abilities/knowledge, shift to a further level of complexity [3]. Following different psychological points of view, growing up implies: adaptation, change of functional meaning; increased complexity; enlargement of the internal knowledge map; abstraction and insight.

CEM09 International Congress on Cognition, Emotion & Motivation, Hammamet, Tunisia, 2-5 Novembre 2009

2008, Contributo in atti di convegno, ENG

A contribution to specification toward truly autonomous robots

Morgavi Giovanna; Marconi Lucia; Morando Mauro

A great deal of current research work in robotics and autonomous systems is still focused on getting an agent to learn to do some task such as recognizing an object or going to a specific place. The learning process may be supervised, unsupervised or a process of occasional reinforcement, but the whole aim in such work is to get the robot to achieve the task that was predefined by the researcher. The next logical step along the road towards truly autonomous robots that can dive in unpredictable environments is to investigate how one might design robots that are capable of `growing up' through experience. A living artifact grows up when its capabilities, abilities/knowledge, shift to a further level of complexity, i.e. the complexity rank of its internal capabilities performs a step forward. Robotics researchers increasingly agree that ideas from nature and self-organization can strongly benefit the design of autonomous robots. In this paper we studied the modalities through which pre-school children (from 4 to 5) tackle with a growing up process: the abstraction. Children of these ages are not supposed to be able to perform the abstraction process, but they have a sufficient knowledge of the natural language that allow the description of the processes they are using when they try to reach the meaning of an abstract sentence. This experiment resulted in some very interesting suggestions on what can be useful for the architecture of an adaptive and evolving robot. The importance of multi-sensor perception, motivation and emotional drives are underlined and, above all, the growing up insights shows similarities to emergent self-organized behaviors.

IAPR Workshop on Cognitive Information Processing, Santorini, Greece, 9-10 Giugno

2008, Contributo in atti di convegno, ENG

Growing Up of Autonomous Agents: an Emergent Phenomenon

Morgavi Giovanna; Marconi Lucia

A fundamental research challenge is the design of robust artifacts that are capable of operating under changing environments and noisy input, and yet exhibit the desired behavior and response time. These systems should be able to adapt and learn how to react to unforeseen scenarios as well as to display properties comparable to biological entities. The turn to nature has brought us many unforeseen great concepts. Biological systems are able to handle many of these challenges with an elegance and efficiency still far beyond current human artifacts. A living artifact grows up when its capabilities, abilities/knowledge, shift to a further level of complexity, i.e. the complexity rank of its internal capabilities performs a step forward. In the attempt to define an architecture for autonomous growing up agents [1]. We conducted an experiment on the abstraction process in children as natural parts of a cognitive system. We found that linguistic growing up involve a number of different trial processes. We identified a fixed number of distinct paths that were crossed by children. Once a given interpretation paths was discovered useless, they tried to follow another path, until the new meaning was emerging. This study generates suggestion about the evolutionary conditions conducive to the emergence of growing up in robots and provides guidelines for designing artificial evolutionary systems displaying spontaneous adaptation abilities. The importance of multi-sensor perception, motivation and emotional drives are underlined and, above all, the growing up insights shows similarities to emergent self-organized behaviors.

CASYS’2007 Eight International Conference on Computing Anticipatory Systems, Liege, Belgium, 5-13 Agosto 2007

DOI: 10.1063/1.3020657

2005, Articolo in rivista, ENG

Growing up: emerging complexity in living being

Morgavi Giovanna; Morando Mauro; Biorci Grazia; Caviglia Daniele

Biological systems live and grow. Many aspects are inherent to the concept of living, such as the adaptation, the interaction with the environment, and the ability to deal with limited resources. Living systems present multiple levels of organization, with elements at one level interacting and aggregating to create more complex behavior at a higher level. In recent years, many new techniques used to investigate the spatio-temporal activity in living being have demonstrated the presence of features common to the behavior of self organizing dynamical systems. Thus a question arises: Is this chaos useful to model living beings? The answer is very difficult to find. Many experimental data support the dynamic chaotic modelling of living systems. Complex behaviors such as perceiving, intending, acting, learning, and remembering arise as metastable spatio-temporal patterns of brain activity that are themselves produced by the cooperative interactions among neural clusters. In this article we present and discuss that question, and we try to give indication for a possible answer, with the aim of defining the basic features of a behavioral kernel for living artefacts.

Cybernetics and systems 36 (4), pp. 379–395

DOI: 10.1080/01969720490929382

2005, Articolo in rivista, ENG

Artificial Emotions for autonomous robot

Morgavi Giovanna; Morando Mauro

The cognitive sciences grew up studying cognition--rational, logical thought. Emotion was traditionally ignored as some leftover from our animal heritage. It turns out that's not true. For example people who have suffered damage to the prefrontal lobes so that they can no longer show emotions are very intelligent and sensible, but they cannot make decisions.' Emotion', or 'affect,' contribute to the information processing system, in a dinstict way from cognition. Autonomous robots needing to deal with unexpected problems that cannot be solved by hard-coded algorithms should have function similar to emotions for the same reason that people do: to keep them safe, make them curious and help them to learn The present work propose an architecture using functionalities similar to those emotions have in human cognition for an evolving robot diving in a real world environment.

WSEAS transactions on systems 11 (4), pp. 1837–1844

2004, Articolo in rivista, ENG

Growing up architecture: specifications from psychology

Morgavi Giovanna; Biorci Grazia

This paper describes some concepts which are important for the creation of autonomous agents capable of growing up. Growing up means that living systems, starting from a pre-structured set of functions, develop competence to better adapt to the environment all life long, from childhood to maturity. A living artefact grows up when its capabilities, abilities/knowledge, shift to a further level of complexity, i.e. the complexity rank of its internal capabilities performs a step forward. We want to define an architecture containing mechanisms which play the same role for autonomous agents as the mechanisms that make humans so successful [1]. In the attempt to define an architecture for autonomous growing up agents, we have been investigating the abstraction process in children as natural parts of a cognitive system. We studied deliberative and non-deliberative (emergent) mental adaptive and growing up mechanisms. A list of functional requirements based on these concepts is then proposed.

WSEAS transactions on systems 6 (3), pp. 2389–2394
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Keyword

growing up

RESULTS FROM 1 TO 8 OF 8